similar to: Speed up sum of outer products?

Hi, I'm new to R and I'm stuck trying to import some data from a .dat file I've been given. The tricky bit for me is that the data has both variable values and labels? The data looks like this, Id=1 time=2011-03-27 19:23:40 start=1.4018 end=1.4017 Id=2 time=2011-03-27 19:23:40 start=1.8046 end=1.8047 Id=1 time=2011-03-27 19:23:50 start=1.4017 end=1.4018 Id=2

Hello! I am running samba 3.0 on fc2 in a win2000 network. I want to use only mandatory profiles in the network, but can't get this to work properly. I have set up a "perfect user" on my local machine", and copied this profile to \\server\netlogon\Default User. I have also made this default profile mandatory by renaming ntuser.dat to ntuser.man. In smb.conf I have added:

Hi everyone, I am doing panel data analysis using the 'plm' package. However, I have noticed that the plm() function reports a different value of R-squared from the R-squared of the lm() function with time-demeaned data. To be clear, I have tried to compute the within model both manually (run an OLS regression with time-demeaned data using lm()) and by using plm(). The two methods give me

Dear R users, I have an unbalanced panel with an average of I=100 individuals and a total of T=1370 time intervals, i.e. T>>I. So far, I have been using the plm package. I wish to estimate a FE model like: res<-plm(x~c+v, data=pdata_frame, effect="twoways", model="within", na.action=na.omit) ?where c varies over i and t, and v represents an exogenous impact on x

Hi, I try to run a bank soft and get this message: err:fixup:NE_LoadSegment NO implementation for EUS.39, setting 0xdeadbeef err:fixup:NE_LoadSegment NO implementation for EUS.46, setting 0xdeadbeef err:fixup:NE_LoadSegment NO implementation for EUS.40, setting 0xdeadbeef err:fixup:NE_LoadSegment NO implementation for EUS.42, setting 0xdeadbeef err:fixup:NE_LoadSegment NO implementation for

Hi, I had some Java code that worked with SJava 0.65 under R 1.8.*. I'm trying to get it to work with R 2.0.0. My JVM is Sun 1.5.0 (running on Fedora Core 2) I downloaded and installed SJava 0.65 in my personal directory using R CMD INSTALL SJava-0.65.tar.gz -l ~/src/Rlibrary and before starting R I sourced RJava.bsh. However after loading the SJava library if do javaConfig() I get

This is a follow-up to bug sent to days ago, which bounced from r-devel because the example was to large. Now example is smaller, and behaviour is as belo, EXEPT that r-windows not any more bombs, so main problem is "xpdrows.data.frame"??? By the way, how to debug this example under windows? debug() doesnt accept the functions used (.Primitive), and R wont run under gdb --- may have

Hi there, Maybe people who know both R and econometrics will be able to answer my questions. I want to run panel regressions in R with fixed-effect. I know two ways to do it. First, I can include factor(grouping_variable) in my regression equation. Second, I plan to subtract group mean from my variables and run OLS panel regression with function lm(). I plan to do it with the second way because

Was'nt sure if this mail got through earlier: I have been having a weird issue with my telco's ISDN PRI occasionally resetting on a incoming call, i suspect it to possibly be a timing issue since some of the incoming call work. This problem happens very frequently. I am using asterisk-1.6.0.1 with libpri-1.4.9, the asterisk server is connected viw TDMoE to a Redfone Fonebridge into

Dear Philipp, this is just a tentative answer because debugging is really not possible without a reproducible example (or, at a very bare minimum, the output from traceback()). Anyway, thank you for reporting this interesting numerical issue; I'll try to replicate some similar behaviour on a similarly dimensioned artificial dataset when I have some time (which might not be soon). As for now,

Hello again Max. A correction to my response from yesterday. Things were better than they seemed. I thought it over, checked Arellano's panel book and Driscoll and Kraay (Rev. Econ. Stud. 1998) and finally realized that vcovSCC does what you want: in fact, despite being born primarily for dealing with cross-sectional correlation, 'SCC' standard errors are robust to "both

Dear R users, I wish to manually demean a panel over time and entities. I tried to code the Wansbeek and Kapteyn (1989) transformation (from Baltagi's book Ch. 9). As a benchmark I use both the pmodel.response() and model.matrix() functions in package plm and the results from using dummy variables. As far as I understood the transformation (Ch.3), Q%*%y (with y being the dependent variable)

dear readers---I struggled with how to do nice fixed-effects regressions in large economic samples for a while. Eventually, I realized that nlme is not really what I needed (too complex), and all I really wanted is the plm package. so, I thought I would share a quick example. ################ sample code to show fixed-effects models? in R # create a sample panel data set with firms and years

Hi, I wanted to change the order of how the plots appear in a multiplot scenario. For example, in the code below: ##### pdf('test.pdf',width=8,height=8) par(mfrow = c(2,2)) for(i in 1:2){ v1 <- sample(1:1000,50) v2 <- sample(1:1000,50) mat <- cbind(v1,v2) plot(v1,v2) boxplot(mat) } dev.off() ####### The plot ordering is that the first row gets filled in first,

Please forgive a statistics question. I know that a simple bivariate linear regression, y=f(x) or in R parlance lm(y~x) can be solved using the variance-covariance matrix: beta(x)=covariance(x,y)/variance(x). I also know that a linear regression with multiple independent variables, for example y=f(x,z) can also be solved using the variance-covariance matrix, but I don't know how to do this.

Is there a way to recover the model matrix that is being used by the plm package? For example, if you run a panel regression with fixed effects, the model matrix would contain the generated dummy variables for the groups. Thanks. Abiel Reinhart This communication is for informational purposes only. I...{{dropped:30}}

Dear Sir/ Madam, I am writing about the panel data for my bachelor degree. I would really appreciate if You could help dealing with R functions. I am trying to estimate the panel data lm model with plm function. When i include 3dummy variables into the regression it dont appear in the sumarry of the model, but when i estimate a simple lm model it appears. Why is it so? What should i do to

Dear R users, Are you worried about the parallel trends assumption in your panel regression? Use fixed effects individual slope models, controlling for heterogeneous trends! I am very pleased to announce that the package feisr is now available on CRAN! CRAN: https://cran.r-project.org/package=feisr GitHub: https://github.com/ruettenauer/feisr The packages feisr provides a function to estimate

Dear R users, Are you worried about the parallel trends assumption in your panel regression? Use fixed effects individual slope models, controlling for heterogeneous trends! I am very pleased to announce that the package feisr is now available on CRAN! CRAN: https://cran.r-project.org/package=feisr GitHub: https://github.com/ruettenauer/feisr The packages feisr provides a function to estimate

I have a data frame called "pose": DESCRIPTION QUANITY CLOSING.PRICE 1 WHEAT May/10 1 467.75 2 WHEAT May/10 2 467.75 3 WHEAT May/10 1 467.75 4 WHEAT May/10 1 467.75 5 COTTON NO.2 May/10 1 78.13 6 COTTON NO.2 May/10 3 78.13 7 COTTON NO.2 May/10 1 78.13